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IoT & IndustrialEnergy
CityBright
AI Smart Street Light Controller based on Quectel BG95
LTE-M street light controller that dims to 10% when no activity is detected, saving 60% energy.
Energy Savings
60%
Range (Radar)
15m
CityBright
Client
A smart city lighting company retrofitting existing municipal street lights with adaptive dimming control to reduce energy costs while maintaining public safety.
Challenge
Developing a drop-in NEMA photocell replacement that adds adaptive lighting control and cellular connectivity to any existing LED street light fixture.
Product Concept & Architecture
The controller uses a Quectel BG95 LTE Cat-M1/BLE SoC. A 60GHz mmWave radar module detects pedestrians, cyclists, and vehicles within 15m. The housing is a standard NEMA 7-pin twist-lock photocell form factor.
Engineering Solution
The firmware implements a zone-based adaptive lighting algorithm: when no activity is detected for 5 minutes, the light dims to 10% output. On radar trigger, the light ramps to 100% over 1.5 seconds. The mmWave radar's point cloud is classified by a TinyML model to distinguish pedestrians from vehicles.
Result
60% average energy savings across pilot deployment. Zero dark zones. NEMA form factor enables 15-minute retrofit installation.
Deep Tech FAQ
What makes the AI Smart Street Light Controller based on Quectel BG95 unique?+
The AI Smart Street Light Controller based on Quectel BG95 leverages custom hardware and edge AI to deliver industry-leading performance and efficiency.
What are the core technical benefits?+
Key benefits include low power consumption, real-time processing, robust connectivity, and a compact form factor tailored for deployment.
Can this architecture be adapted for other use cases?+
Absolutely. The underlying methodology is modular and can be retargeted for various applications with minimal redesign.
Project Profile
Services Delivered
Hardware DesignEmbedded SoftwareRF Design
Core Technologies
LTE-M/NB-IoTTinyMLRTOS
Silicon & Vendors
QuectelSTMicroelectronics
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